# !pip install git+https://github.com/alberanid/imdbpy
# !pip install pandas
# !pip install numpy
# !pip install matplotlib
# !pip install seaborn
# !pip install pandas_profiling --upgrade
# !pip install plotly
# ! pip install wordcloud
# ! pip install Flask

# Import Dataset
# Import File from Loacal Drive
# from google.colab import files
# data_to_load = files.upload()
# from google.colab import drive
# drive.mount('/content/drive')

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
import collections
import plotly.express as px
import plotly.graph_objects as go
import nltk
import re
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.probability import FreqDist
from nltk.util import ngrams
from plotly.subplots import make_subplots
from plotly.offline import iplot, init_notebook_mode
from wordcloud import WordCloud, STOPWORDS
from pandas_profiling import ProfileReport
%matplotlib inline
warnings.filterwarnings("ignore")

nltk.download('all')

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[nltk_data]    | Downloading package porter_test to
[nltk_data]    |     C:\Users\pawan\AppData\Roaming\nltk_data...
[nltk_data]    |   Package porter_test is already up-to-date!
[nltk_data]    | Downloading package wmt15_eval to
[nltk_data]    |     C:\Users\pawan\AppData\Roaming\nltk_data...
[nltk_data]    |   Package wmt15_eval is already up-to-date!
[nltk_data]    | Downloading package mwa_ppdb to
[nltk_data]    |     C:\Users\pawan\AppData\Roaming\nltk_data...
[nltk_data]    |   Package mwa_ppdb is already up-to-date!
[nltk_data]    | 
[nltk_data]  Done downloading collection all

True

# path = '/content/drive/MyDrive/Files/'

path = 'C:\\Users\\pawan\\OneDrive\\Desktop\\ott\\Data\\'
 
df_tvshows = pd.read_csv(path + 'otttvshows.csv')
 
df_tvshows.head()

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	Language	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type
0	1	Snowpiercer	2013	18+	6.9	94%	NaN	Daveed Diggs,Iddo Goldberg,Mickey Sumner,Aliso...	Action,Drama,Sci-Fi,Thriller	United States	English	Set seven years after the world has become a f...	60.0	tv series	3.0	1	0	0	0	1
1	2	Philadelphia	1993	13+	8.8	80%	NaN	Charlie Day,Glenn Howerton,Rob McElhenney,Kait...	Comedy	United States	English	The gang, 5 raging alcoholic, narcissists run ...	22.0	tv series	18.0	1	0	0	0	1
2	3	Roma	2018	18+	8.7	93%	NaN	Kevin McKidd,Ray Stevenson,Polly Walker,Kerry ...	Action,Drama,History,Romance,War	United Kingdom,United States	English	In this British historical drama, the turbulen...	52.0	tv series	2.0	1	0	0	0	1
3	4	Amy	2015	18+	7.0	87%	NaN	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	English	A family drama focused on three generations of...	60.0	tv series	6.0	1	0	1	1	1
4	5	The Young Offenders	2016	NaN	8.0	100%	NaN	Alex Murphy,Chris Walley,Hilary Rose,Dominic M...	Comedy	United Kingdom,Ireland	English	NaN	30.0	tv series	3.0	1	0	0	0	1

# profile = ProfileReport(df_tvshows)
# profile

def data_investigate(df):
    print('No of Rows : ', df.shape[0])
    print('No of Coloums : ', df.shape[1])
    print('**'*25)
    print('Colums Names : \n', df.columns)
    print('**'*25)
    print('Datatype of Columns : \n', df.dtypes)
    print('**'*25)
    print('Missing Values : ')
    c = df.isnull().sum()
    c = c[c > 0]
    print(c)
    print('**'*25)
    print('Missing vaules %age wise :\n')
    print((100*(df.isnull().sum()/len(df.index))))
    print('**'*25)
    print('Pictorial Representation : ')
    plt.figure(figsize = (10, 10))
    sns.heatmap(df.isnull(), yticklabels = False, cbar = False)
    plt.show()

data_investigate(df_tvshows)

No of Rows :  5432
No of Coloums :  20
**************************************************
Colums Names : 
 Index(['ID', 'Title', 'Year', 'Age', 'IMDb', 'Rotten Tomatoes', 'Directors',
       'Cast', 'Genres', 'Country', 'Language', 'Plotline', 'Runtime', 'Kind',
       'Seasons', 'Netflix', 'Hulu', 'Prime Video', 'Disney+', 'Type'],
      dtype='object')
**************************************************
Datatype of Columns : 
 ID                   int64
Title               object
Year                 int64
Age                 object
IMDb               float64
Rotten Tomatoes     object
Directors           object
Cast                object
Genres              object
Country             object
Language            object
Plotline            object
Runtime            float64
Kind                object
Seasons            float64
Netflix              int64
Hulu                 int64
Prime Video          int64
Disney+              int64
Type                 int64
dtype: object
**************************************************
Missing Values : 
Age                1954
IMDb                556
Rotten Tomatoes    4194
Directors          5158
Cast                486
Genres              323
Country             549
Language            638
Plotline           2493
Runtime            1410
Seasons             679
dtype: int64
**************************************************
Missing vaules %age wise :

ID                  0.000000
Title               0.000000
Year                0.000000
Age                35.972018
IMDb               10.235641
Rotten Tomatoes    77.209131
Directors          94.955817
Cast                8.946981
Genres              5.946244
Country            10.106775
Language           11.745214
Plotline           45.894698
Runtime            25.957290
Kind                0.000000
Seasons            12.500000
Netflix             0.000000
Hulu                0.000000
Prime Video         0.000000
Disney+             0.000000
Type                0.000000
dtype: float64
**************************************************
Pictorial Representation : 

# ID
# df_tvshows = df_tvshows.drop(['ID'], axis = 1)
 
# Age
df_tvshows.loc[df_tvshows['Age'].isnull() & df_tvshows['Disney+'] == 1, "Age"] = '13'
# df_tvshows.fillna({'Age' : 18}, inplace = True)
df_tvshows.fillna({'Age' : 'NR'}, inplace = True)
df_tvshows['Age'].replace({'all': '0'}, inplace = True)
df_tvshows['Age'].replace({'7+': '7'}, inplace = True)
df_tvshows['Age'].replace({'13+': '13'}, inplace = True)
df_tvshows['Age'].replace({'16+': '16'}, inplace = True)
df_tvshows['Age'].replace({'18+': '18'}, inplace = True)
# df_tvshows['Age'] = df_tvshows['Age'].astype(int)
 
# IMDb
# df_tvshows.fillna({'IMDb' : df_tvshows['IMDb'].mean()}, inplace = True)
# df_tvshows.fillna({'IMDb' : df_tvshows['IMDb'].median()}, inplace = True)
df_tvshows.fillna({'IMDb' : "NA"}, inplace = True)
 
# Rotten Tomatoes
df_tvshows['Rotten Tomatoes'] = df_tvshows['Rotten Tomatoes'][df_tvshows['Rotten Tomatoes'].notnull()].str.replace('%', '').astype(int)
# df_tvshows['Rotten Tomatoes'] = df_tvshows['Rotten Tomatoes'][df_tvshows['Rotten Tomatoes'].notnull()].astype(int)
# df_tvshows.fillna({'Rotten Tomatoes' : df_tvshows['Rotten Tomatoes'].mean()}, inplace = True)
# df_tvshows.fillna({'Rotten Tomatoes' : df_tvshows['Rotten Tomatoes'].median()}, inplace = True)
# df_tvshows['Rotten Tomatoes'] = df_tvshows['Rotten Tomatoes'].astype(int)
df_tvshows.fillna({'Rotten Tomatoes' : "NA"}, inplace = True)
 
# Directors
# df_tvshows = df_tvshows.drop(['Directors'], axis = 1)
df_tvshows.fillna({'Directors' : "NA"}, inplace = True)
 
# Cast
df_tvshows.fillna({'Cast' : "NA"}, inplace = True)
 
# Genres
df_tvshows.fillna({'Genres': "NA"}, inplace = True)
 
# Country
df_tvshows.fillna({'Country': "NA"}, inplace = True)
 
# Language
df_tvshows.fillna({'Language': "NA"}, inplace = True)
 
# Plotline
df_tvshows.fillna({'Plotline': "NA"}, inplace = True)
 
# Runtime
# df_tvshows.fillna({'Runtime' : df_tvshows['Runtime'].mean()}, inplace = True)
# df_tvshows['Runtime'] = df_tvshows['Runtime'].astype(int)
df_tvshows.fillna({'Runtime' : "NA"}, inplace = True)
 
# Kind
# df_tvshows.fillna({'Kind': "NA"}, inplace = True)
 
# Type
# df_tvshows.fillna({'Type': "NA"}, inplace = True)
# df_tvshows = df_tvshows.drop(['Type'], axis = 1)
 
# Seasons
# df_tvshows.fillna({'Seasons': 1}, inplace = True)
df_tvshows.fillna({'Seasons': "NA"}, inplace = True)
# df_tvshows = df_tvshows.drop(['Seasons'], axis = 1)
# df_tvshows['Seasons'] = df_tvshows['Seasons'].astype(int)
# df_tvshows.fillna({'Seasons' : df_tvshows['Seasons'].mean()}, inplace = True)
# df_tvshows['Seasons'] = df_tvshows['Seasons'].astype(int)
 
# Service Provider
df_tvshows['Service Provider'] = df_tvshows.loc[:, ['Netflix', 'Prime Video', 'Disney+', 'Hulu']].idxmax(axis = 1)
# df_tvshows.drop(['Netflix','Prime Video','Disney+','Hulu'], axis = 1)

# Removing Duplicate and Missing Entries
df_tvshows.dropna(how = 'any', inplace = True)
df_tvshows.drop_duplicates(inplace = True)

data_investigate(df_tvshows)

No of Rows :  5432
No of Coloums :  21
**************************************************
Colums Names : 
 Index(['ID', 'Title', 'Year', 'Age', 'IMDb', 'Rotten Tomatoes', 'Directors',
       'Cast', 'Genres', 'Country', 'Language', 'Plotline', 'Runtime', 'Kind',
       'Seasons', 'Netflix', 'Hulu', 'Prime Video', 'Disney+', 'Type',
       'Service Provider'],
      dtype='object')
**************************************************
Datatype of Columns : 
 ID                   int64
Title               object
Year                 int64
Age                 object
IMDb                object
Rotten Tomatoes     object
Directors           object
Cast                object
Genres              object
Country             object
Language            object
Plotline            object
Runtime             object
Kind                object
Seasons              int32
Netflix              int64
Hulu                 int64
Prime Video          int64
Disney+              int64
Type                 int64
Service Provider    object
dtype: object
**************************************************
Missing Values : 
Series([], dtype: int64)
**************************************************
Missing vaules %age wise :

ID                  0.0
Title               0.0
Year                0.0
Age                 0.0
IMDb                0.0
Rotten Tomatoes     0.0
Directors           0.0
Cast                0.0
Genres              0.0
Country             0.0
Language            0.0
Plotline            0.0
Runtime             0.0
Kind                0.0
Seasons             0.0
Netflix             0.0
Hulu                0.0
Prime Video         0.0
Disney+             0.0
Type                0.0
Service Provider    0.0
dtype: float64
**************************************************
Pictorial Representation : 

df_tvshows.head()

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider
0	1	Snowpiercer	2013	18	6.9	94	NA	Daveed Diggs,Iddo Goldberg,Mickey Sumner,Aliso...	Action,Drama,Sci-Fi,Thriller	United States	...	Set seven years after the world has become a f...	60	tv series	3	1	0	0	0	1	Netflix
1	2	Philadelphia	1993	13	8.8	80	NA	Charlie Day,Glenn Howerton,Rob McElhenney,Kait...	Comedy	United States	...	The gang, 5 raging alcoholic, narcissists run ...	22	tv series	18	1	0	0	0	1	Netflix
2	3	Roma	2018	18	8.7	93	NA	Kevin McKidd,Ray Stevenson,Polly Walker,Kerry ...	Action,Drama,History,Romance,War	United Kingdom,United States	...	In this British historical drama, the turbulen...	52	tv series	2	1	0	0	0	1	Netflix
3	4	Amy	2015	18	7	87	NA	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	...	A family drama focused on three generations of...	60	tv series	6	1	0	1	1	1	Netflix
4	5	The Young Offenders	2016	NR	8	100	NA	Alex Murphy,Chris Walley,Hilary Rose,Dominic M...	Comedy	United Kingdom,Ireland	...	NA	30	tv series	3	1	0	0	0	1	Netflix

5 rows × 21 columns

df_tvshows.describe()

	ID	Year	Seasons	Netflix	Hulu	Prime Video	Disney+	Type
count	5432.000000	5432.000000	5432.000000	5432.000000	5432.000000	5432.000000	5432.000000	5432.0
mean	2716.500000	2010.668446	3.012334	0.341311	0.293999	0.403351	0.033689	1.0
std	1568.227662	11.726176	4.105634	0.474193	0.455633	0.490615	0.180445	0.0
min	1.000000	1901.000000	1.000000	0.000000	0.000000	0.000000	0.000000	1.0
25%	1358.750000	2009.000000	1.000000	0.000000	0.000000	0.000000	0.000000	1.0
50%	2716.500000	2014.000000	1.000000	0.000000	0.000000	0.000000	0.000000	1.0
75%	4074.250000	2017.000000	3.000000	1.000000	1.000000	1.000000	0.000000	1.0
max	5432.000000	2020.000000	53.000000	1.000000	1.000000	1.000000	1.000000	1.0

df_tvshows.corr()

	ID	Year	Seasons	Netflix	Hulu	Prime Video	Disney+	Type
ID	1.000000	-0.031346	-0.048292	-0.646330	0.034293	0.441264	0.195409	NaN
Year	-0.031346	1.000000	-0.219170	0.222316	-0.065807	-0.198675	-0.022741	NaN
Seasons	-0.048292	-0.219170	1.000000	-0.052478	0.223957	-0.061613	0.001924	NaN
Netflix	-0.646330	0.222316	-0.052478	1.000000	-0.366515	-0.515086	-0.119344	NaN
Hulu	0.034293	-0.065807	0.223957	-0.366515	1.000000	-0.377374	-0.075701	NaN
Prime Video	0.441264	-0.198675	-0.061613	-0.515086	-0.377374	1.000000	-0.151442	NaN
Disney+	0.195409	-0.022741	0.001924	-0.119344	-0.075701	-0.151442	1.000000	NaN
Type	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

# df_tvshows.sort_values('Year', ascending = True)
# df_tvshows.sort_values('IMDb', ascending = False)

# df_tvshows.to_csv(path_or_buf= '/content/drive/MyDrive/Files/updated_otttvshows.csv', index = False)
 
# path = '/content/drive/MyDrive/Files/'
 
# udf_tvshows = pd.read_csv(path + 'updated_otttvshows.csv')
 
# udf_tvshows

# df_netflix_tvshows = df_tvshows.loc[(df_tvshows['Netflix'] > 0)]
# df_hulu_tvshows = df_tvshows.loc[(df_tvshows['Hulu'] > 0)]
# df_prime_video_tvshows = df_tvshows.loc[(df_tvshows['Prime Video'] > 0)]
# df_disney_tvshows = df_tvshows.loc[(df_tvshows['Disney+'] > 0)]

df_netflix_only_tvshows = df_tvshows[(df_tvshows['Netflix'] == 1) & (df_tvshows['Hulu'] == 0) & (df_tvshows['Prime Video'] == 0 ) & (df_tvshows['Disney+'] == 0)]
df_hulu_only_tvshows = df_tvshows[(df_tvshows['Netflix'] == 0) & (df_tvshows['Hulu'] == 1) & (df_tvshows['Prime Video'] == 0 ) & (df_tvshows['Disney+'] == 0)]
df_prime_video_only_tvshows = df_tvshows[(df_tvshows['Netflix'] == 0) & (df_tvshows['Hulu'] == 0) & (df_tvshows['Prime Video'] == 1 ) & (df_tvshows['Disney+'] == 0)]
df_disney_only_tvshows = df_tvshows[(df_tvshows['Netflix'] == 0) & (df_tvshows['Hulu'] == 0) & (df_tvshows['Prime Video'] == 0 ) & (df_tvshows['Disney+'] == 1)]

df_tvshows_ott = df_tvshows.copy()

df_tvshows_ott.drop(df_tvshows_ott.loc[df_tvshows_ott['Title'] == "NA"].index, inplace = True)
# df_tvshows_ott = df_tvshows_ott[df_tvshows_ott.Title != "NA"]

# Creating distinct dataframes only with the tvshows present on individual streaming platforms
netflix_ott_tvshows = df_tvshows_ott.loc[df_tvshows_ott['Netflix'] == 1]
hulu_ott_tvshows = df_tvshows_ott.loc[df_tvshows_ott['Hulu'] == 1]
prime_video_ott_tvshows = df_tvshows_ott.loc[df_tvshows_ott['Prime Video'] == 1]
disney_ott_tvshows = df_tvshows_ott.loc[df_tvshows_ott['Disney+'] == 1]

df_tvshows_ott_group = df_tvshows_ott.copy()

plt.figure(figsize = (10, 10))
corr = df_tvshows_ott.corr()
# Plot figsize
fig, ax = plt.subplots(figsize=(10, 8))
# Generate Heat Map, allow annotations and place floats in map
sns.heatmap(corr, cmap = 'magma', annot = True, fmt = ".2f")
# Apply xticks
plt.xticks(range(len(corr.columns)), corr.columns);
# Apply yticks
plt.yticks(range(len(corr.columns)), corr.columns)
# show plot
plt.show()
fig.show()

<Figure size 720x720 with 0 Axes>

print('\nTV Shows Available on All Platfroms Are : \n')
df_tvshows_ott.head(5)

TV Shows Available on All Platfroms Are : 

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider
0	1	Snowpiercer	2013	18	6.9	94	NA	Daveed Diggs,Iddo Goldberg,Mickey Sumner,Aliso...	Action,Drama,Sci-Fi,Thriller	United States	...	Set seven years after the world has become a f...	60	tv series	3	1	0	0	0	1	Netflix
1	2	Philadelphia	1993	13	8.8	80	NA	Charlie Day,Glenn Howerton,Rob McElhenney,Kait...	Comedy	United States	...	The gang, 5 raging alcoholic, narcissists run ...	22	tv series	18	1	0	0	0	1	Netflix
2	3	Roma	2018	18	8.7	93	NA	Kevin McKidd,Ray Stevenson,Polly Walker,Kerry ...	Action,Drama,History,Romance,War	United Kingdom,United States	...	In this British historical drama, the turbulen...	52	tv series	2	1	0	0	0	1	Netflix
3	4	Amy	2015	18	7	87	NA	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	...	A family drama focused on three generations of...	60	tv series	6	1	0	1	1	1	Netflix
4	5	The Young Offenders	2016	NR	8	100	NA	Alex Murphy,Chris Walley,Hilary Rose,Dominic M...	Comedy	United Kingdom,Ireland	...	NA	30	tv series	3	1	0	0	0	1	Netflix

5 rows × 21 columns

print('\nTV Shows Available on Netflix Are : \n')
netflix_ott_tvshows.head(5)

TV Shows Available on Netflix Are : 

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider
0	1	Snowpiercer	2013	18	6.9	94	NA	Daveed Diggs,Iddo Goldberg,Mickey Sumner,Aliso...	Action,Drama,Sci-Fi,Thriller	United States	...	Set seven years after the world has become a f...	60	tv series	3	1	0	0	0	1	Netflix
1	2	Philadelphia	1993	13	8.8	80	NA	Charlie Day,Glenn Howerton,Rob McElhenney,Kait...	Comedy	United States	...	The gang, 5 raging alcoholic, narcissists run ...	22	tv series	18	1	0	0	0	1	Netflix
2	3	Roma	2018	18	8.7	93	NA	Kevin McKidd,Ray Stevenson,Polly Walker,Kerry ...	Action,Drama,History,Romance,War	United Kingdom,United States	...	In this British historical drama, the turbulen...	52	tv series	2	1	0	0	0	1	Netflix
3	4	Amy	2015	18	7	87	NA	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	...	A family drama focused on three generations of...	60	tv series	6	1	0	1	1	1	Netflix
4	5	The Young Offenders	2016	NR	8	100	NA	Alex Murphy,Chris Walley,Hilary Rose,Dominic M...	Comedy	United Kingdom,Ireland	...	NA	30	tv series	3	1	0	0	0	1	Netflix

5 rows × 21 columns

print('\nTV Shows Available on Hulu Are : \n')
hulu_ott_tvshows.head(5)

TV Shows Available on Hulu Are : 

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider
16	17	The Oath	2016	NR	6.6	88	NA	Ryan Kwanten,Katrina Law,Cory Hardrict,Joseph ...	Crime,Drama	United States	...	NA	60	tv series	2	1	1	0	0	1	Netflix
29	30	Zapped	2014	0	6.8	6	Peter DeLuise	James Buckley,Kenneth Collard,Louis Emerick,Pa...	Comedy,Fantasy	United Kingdom	...	NA	30	tv series	3	1	1	0	1	1	Netflix
101	102	Vice	2018	18	8.3	46	NA	Julia Louis-Dreyfus,Anna Chlumsky,Tony Hale,Re...	Comedy	United States	...	Politics is about people, former Sen. Selina M...	28	tv series	7	0	1	0	0	1	Hulu
102	103	Get Smart	2008	13	8.2	51	Peter Segal	Don Adams,Barbara Feldon,Edward Platt,Robert K...	Action,Adventure,Comedy,Crime,Family,Mystery,S...	United States	...	Maxwell Smart is a bumbling secret agent, assi...	25	tv series	5	0	1	0	0	1	Hulu
103	104	Amazing Grace	2018	0	7.1	67	Michael Apted	Kate Jenkinson,Sigrid Thornton,Alex Dimitriade...	Drama	Australia	...	The series centres on midwife Grace and her pa...	118	tv series	1	0	1	0	0	1	Hulu

5 rows × 21 columns

print('\nTV Shows Available on Prime Video Are : \n')
prime_video_ott_tvshows.head(5)

TV Shows Available on Prime Video Are : 

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider
3	4	Amy	2015	18	7	87	NA	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	...	A family drama focused on three generations of...	60	tv series	6	1	0	1	1	1	Netflix
7	8	Retribution	2015	NR	7	28	NA	Joanna Vanderham,John Lynch,Joe Dempsie,Julie ...	Drama,Mystery,Thriller	United Kingdom	...	Childhood sweethearts Adam Elliot and Grace Do...	231	tv series	1	1	0	1	0	1	Netflix
15	16	Eli	2019	18	7.9	46	NA	Sacha Baron Cohen,Hadar Ratzon Rotem,Yael Eita...	Drama,History	France	...	Israel, 1959. The Mossad are desperate to embe...	53	tv series	1	1	0	1	0	1	Netflix
17	18	Zero	2018	NR	5.5	88	Aanand L. Rai	Giuseppe Dave Seke,Haroun Fall,Beatrice Grannò...	Action,Comedy,Drama,Fantasy,Sci-Fi	Italy	...	NA	164	tv series	1	1	0	1	0	1	Netflix
18	19	The Outsider	2018	NR	7.8	36	NA	Ben Mendelsohn,Bill Camp,Jeremy Bobb,Mare Winn...	Crime,Drama,Fantasy,Mystery,Thriller	United States	...	The Outsider begins with a seemingly straightf...	60	tv series	1	1	0	1	0	1	Netflix

5 rows × 21 columns

print('\nTV Shows Available on Disney+ Are : \n')
disney_ott_tvshows.head(5)

TV Shows Available on Disney+ Are : 

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Plotline	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider
3	4	Amy	2015	18	7	87	NA	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	...	A family drama focused on three generations of...	60	tv series	6	1	0	1	1	1	Netflix
29	30	Zapped	2014	0	6.8	6	Peter DeLuise	James Buckley,Kenneth Collard,Louis Emerick,Pa...	Comedy,Fantasy	United Kingdom	...	NA	30	tv series	3	1	1	0	1	1	Netflix
482	483	Avatar	2009	13	9.2	82	NA	Dee Bradley Baker,Zach Tyler,Mae Whitman,Jack ...	Animation,Action,Adventure,Family,Fantasy,Mystery	United States	...	In a suburban fantasy world, two teenage elf b...	23	tv series	3	0	0	0	1	1	Disney+
483	484	Invincible	2006	7	8.8	72	Angelina Jolie	Steven Yeun,Sandra Oh,J.K. Simmons,Zazie Beetz...	Animation,Action,Adventure,Drama,Fantasy,Horro...	United States	...	In February of 1952, one of the worst storms t...	137	tv series	1	0	0	0	1	1	Disney+
484	485	High School Musical	2006	0	7.4	63	Kenny Ortega	Joshua Bassett,Olivia Rodrigo,Matt Cornett,Jul...	Comedy,Drama,Musical	United States	...	The famous race car Lightning McQueen and his ...	31	tv series	2	0	0	0	1	1	Disney+

5 rows × 21 columns

print(f'''
      Total '{df_tvshows_ott['Title'].count()}' Titles are available on All Platforms, out of Which,\n
      Total '{netflix_ott_tvshows['Title'].count()}' Titles are available on 'Netflix'
      Total '{hulu_ott_tvshows['Title'].count()}' Titles are available on 'Hulu'
      Total '{prime_video_ott_tvshows['Title'].count()}' Titles are available on 'Prime video'
      Total '{disney_ott_tvshows['Title'].count()}' Titles are available on 'Disney+'
      ''')

      Total '5432' Titles are available on All Platforms, out of Which,

      Total '1854' Titles are available on 'Netflix'
      Total '1597' Titles are available on 'Hulu'
      Total '2191' Titles are available on 'Prime video'
      Total '183' Titles are available on 'Disney+'
      

Platform = ['Netflix', 'Hulu', 'Prime Video', 'Disney+']

Count = [netflix_ott_tvshows['Title'].count(),
         hulu_ott_tvshows['Title'].count(),
         prime_video_ott_tvshows['Title'].count(),
         disney_ott_tvshows['Title'].count()]
 
fig = px.pie(names = Platform,
             values = Count,
             title = 'TV Shows Count Of Different Platforms',
             color_discrete_sequence = px.colors.sequential.Teal)

fig.update_traces(textposition = 'inside',
                  textinfo = 'percent + label') 
fig.show()

df_tvshows_ott['OTT Count'] = df_tvshows_ott['Netflix'] + df_tvshows_ott['Hulu'] + df_tvshows_ott['Prime Video'] + df_tvshows_ott['Disney+']

(df_tvshows_ott['OTT Count'].value_counts()/df_tvshows_ott.shape[0])*100

1    93.372607
2     6.019882
3     0.607511
Name: OTT Count, dtype: float64

print(f'''
      Total '{df_tvshows_ott[df_tvshows_ott['OTT Count'] == 4].shape[0]}' Titles are available on All Platforms
      Total '{df_tvshows_ott[df_tvshows_ott['OTT Count'] == 3].shape[0]}' Titles are available on at least 3 Platforms
      Total '{df_tvshows_ott[df_tvshows_ott['OTT Count'] == 2].shape[0]}' Titles are available on at least 2 Platforms
      Total '{df_tvshows_ott[df_tvshows_ott['OTT Count'] == 1].shape[0]}' Titles are available on at least 1 Platforms
      ''')

      Total '0' Titles are available on All Platforms
      Total '33' Titles are available on at least 3 Platforms
      Total '327' Titles are available on at least 2 Platforms
      Total '5072' Titles are available on at least 1 Platforms
      

# TV Shows Available on All Platforms

# df_tvshows_ott[(df_tvshows_ott['Netflix'] == 1) & (df_tvshows_ott['Hulu'] == 1) & (df_tvshows_ott['Prime Video'] == 1) & (df_tvshows_ott['Disney+'] == 1)]
print('\nTotal ', df_tvshows_ott[df_tvshows_ott['OTT Count'] == 4].shape[0], ' Titles are available on All Platforms\n')
tvshows_on_4_platforms = df_tvshows_ott[df_tvshows_ott['OTT Count'] == 4]
tvshows_on_4_platforms

Total  0  Titles are available on All Platforms

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count

0 rows × 22 columns

# TV Shows Available on at least 3 Platforms

print('\nTotal ', df_tvshows_ott[df_tvshows_ott['OTT Count'] == 3].shape[0], ' Titles are available on at least 3 Platforms\n')
tvshows_on_3_platforms = df_tvshows_ott[df_tvshows_ott['OTT Count'] == 3]
tvshows_on_3_platforms

Total  33  Titles are available on at least 3 Platforms

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
3	4	Amy	2015	18	7	87	NA	Amy Brenneman,Richard T. Jones,Jessica Tuck,Ma...	Drama	United States	...	60	tv series	6	1	0	1	1	1	Netflix	3
29	30	Zapped	2014	0	6.8	6	Peter DeLuise	James Buckley,Kenneth Collard,Louis Emerick,Pa...	Comedy,Fantasy	United Kingdom	...	30	tv series	3	1	1	0	1	1	Netflix	3
522	523	Parks and Recreation	2009	7	8.6	93	NA	Amy Poehler,Nick Offerman,Aubrey Plaza,Jim O'H...	Comedy	United States	...	22	tv series	7	1	1	1	0	1	Netflix	3
566	567	Star Trek: The Next Generation	1987	7	8.6	91	NA	Patrick Stewart,Jonathan Frakes,LeVar Burton,M...	Action,Adventure,Mystery,Sci-Fi	United States	...	44	tv series	7	1	1	1	0	1	Netflix	3
574	575	The Good Wife	2009	7	8.3	93	NA	Julianna Margulies,Matt Czuchry,Christine Bara...	Crime,Drama,Mystery	United States	...	43	tv series	7	1	1	1	0	1	Netflix	3
591	592	Burn Notice	2007	7	7.9	88	NA	Jeffrey Donovan,Gabrielle Anwar,Bruce Campbell...	Action,Crime,Drama,Mystery,Thriller	United States	...	44	tv series	7	1	1	1	0	1	Netflix	3
596	597	American Horror Story	2011	18	8	NA	NA	Evan Peters,Sarah Paulson,Denis O'Hare,Kathy B...	Drama,Horror,Thriller	United States	...	60	tv series	13	1	1	1	0	1	Netflix	3
602	603	Star Trek	1966	7	8.3	80	NA	Leonard Nimoy,William Shatner,DeForest Kelley,...	Action,Adventure,Sci-Fi	United States	...	50	tv series	3	1	1	1	0	1	Netflix	3
626	627	Mushi-Shi	2005	16	8.5	100	NA	Yûto Nakano,Travis Willingham,Kôjun Itô,Jennif...	Animation,Drama,Fantasy,Horror,Mystery,Thriller	Japan	...	25	tv series	1	1	1	1	0	1	Netflix	3
643	644	Star Trek: Deep Space Nine	1993	7	8	91	NA	Avery Brooks,Rene Auberjonois,Cirroc Lofton,Al...	Action,Adventure,Drama,Sci-Fi	United States	...	45	tv series	7	1	1	1	0	1	Netflix	3
654	655	Law & Order: Special Victims Unit	1999	7	8	78	NA	Mariska Hargitay,Ice-T,Dann Florek,Richard Bel...	Crime,Drama,Mystery,Thriller	United States	...	60	tv series	24	1	1	1	0	1	Netflix	3
681	682	Star Trek: Voyager	1995	7	7.8	76	NA	Kate Mulgrew,Robert Beltran,Roxann Dawson,Robe...	Action,Adventure,Sci-Fi	United States	...	44	tv series	7	1	1	1	0	1	Netflix	3
706	707	Merlin	2008	16	7.9	85	NA	John Hurt,Colin Morgan,Bradley James,Richard W...	Adventure,Drama,Fantasy	United Kingdom	...	45	tv series	5	1	1	1	0	1	Netflix	3
741	742	Pokémon	1997	0	7.5	NA	NA	Ikue Ôtani,Rica Matsumoto,Rodger Parsons,Shin'...	Animation,Action,Adventure,Comedy,Family,Fantasy	Japan	...	24	tv series	23	1	1	1	0	1	Netflix	3
742	743	Cheers	1982	7	7.8	NA	NA	Ted Danson,Rhea Perlman,John Ratzenberger,Geor...	Comedy,Drama	United States	...	22	tv series	11	1	1	1	0	1	Netflix	3
744	745	Star Trek: Enterprise	2001	7	7.5	57	NA	Scott Bakula,John Billingsley,Jolene Blalock,D...	Action,Adventure,Drama,Sci-Fi	United States	...	60	tv series	4	1	1	1	0	1	Netflix	3
782	783	Descendants of the Sun	2016	16	8.3	NA	NA	Song Joong-Ki,Song Hye-Kyo,Jin Goo,Kim Ji-Won,...	Action,Comedy,Drama,Romance	South Korea	...	60	tv series	1	1	1	1	0	1	Netflix	3
786	787	Ancient Aliens	2010	7	7.3	NA	NA	Robert Clotworthy,Giorgio A. Tsoukalos,David C...	Documentary,Fantasy,History,Sci-Fi	United States	...	42	tv series	16	1	1	1	0	1	Netflix	3
830	831	Rake	2010	16	8.5	100	NA	Richard Roxburgh,Matt Day,Kate Box,Caroline Br...	Comedy,Drama	Australia	...	60	tv series	5	1	1	1	0	1	Netflix	3
839	840	H2O: Just Add Water	2006	7	7.2	NA	NA	Cariba Heine,Phoebe Tonkin,Angus McLaren,Burge...	Drama,Family,Fantasy	Australia	...	23	tv series	3	1	1	1	0	1	Netflix	3
945	946	Forensic Files	1996	16	8.8	NA	NA	Peter Thomas,Tom Bevel,Skip Palenik,Lowell Lev...	Documentary,Crime	United States	...	30	tv series	15	1	1	1	0	1	Netflix	3
995	996	America's Funniest Home Videos	1989	0	6.2	NA	NA	Jess Harnell,Tom Bergeron,Bob Saget,Ernie Ande...	Comedy,Family,Reality-TV	United States	...	30	tv series	31	1	1	0	1	1	Netflix	3
1043	1044	Yu-Gi-Oh!	1998	7	7.2	NA	NA	Dan Green,Wayne Grayson,Amy Birnbaum,Eric Stua...	Animation,Action,Adventure,Family,Fantasy	Japan	...	24	tv series	5	1	1	1	0	1	Netflix	3
1162	1163	Sonic x	2003	7	6.2	NA	NA	Gabriella Lewis,Jun'ichi Kanemaru,Sanae Kobaya...	Animation,Action,Adventure,Comedy,Family,Fanta...	Japan	...	30	tv series	3	1	1	1	0	1	Netflix	3
1326	1327	Hangar 1: The UFO Files	2015	7	7.3	NA	NA	Cornell Womack,John Ventre,Jeremy Ray,Nik Petc...	Mystery,Reality-TV,Sci-Fi	NA	...	NA	tv series	2	1	1	1	0	1	Netflix	3
1370	1371	Pocoyo	2005	0	7.4	NA	NA	Stephen Fry,Alex Marty,Montana Smedley,Stephen...	Animation,Comedy,Family	Spain,United Kingdom	...	7	tv series	4	1	1	1	0	1	Netflix	3
1438	1439	Yu-Gi-Oh! Arc-V	2014	7	6.2	NA	NA	Mike Liscio,Alyson Leigh Rosenfeld,Daniel J. E...	Animation,Adventure,Fantasy	Japan,Canada	...	20	tv series	3	1	1	1	0	1	Netflix	3
1441	1442	America's Book of Secrets	2012	16	6.8	NA	NA	Barry Aird,Jonathan Adams,Alex Jones,Ronald Ke...	Documentary	United States	...	44	tv series	3	1	1	1	0	1	Netflix	3
1676	1677	Oddbods	2015	7	6.4	NA	NA	Marlon Dance-Hooi,Nadia Ramlee,Jeremy Linn,Su-...	Animation,Comedy,Family	United Kingdom,Singapore	...	NA	tv series	6	1	1	1	0	1	Netflix	3
1734	1735	Yu-Gi-Oh! Zexal	2011	7	4.9	NA	NA	Marc Thompson,Sean Schemmel,Eileen Stevens,Mic...	Animation,Action,Comedy,Fantasy,Sci-Fi	Japan	...	NA	tv series	6	1	1	1	0	1	Netflix	3
1764	1765	LEGO Friends	2012	0	5.3	NA	NA	Alexa Kahn,Rachelle Heger,Erica Mendez,Mariann...	Animation	NA	...	4	tv series	4	1	1	1	0	1	Netflix	3
1981	1982	Pororo the Little Penguin	2003	0	5.9	NA	NA	So-yeong Hong,Goo Ja-Hyeong,Hwan Chin Kim,Mi J...	Animation,Family	South Korea	...	NA	tv series	6	1	1	1	0	1	Netflix	3
2028	2029	Tayo the Little Bus	2010	NR	5.6	NA	NA	Jul Kohler,Patricia Kalis,Aramis Merlin,Tea Wa...	Animation	South Korea	...	NA	tv series	5	1	1	1	0	1	Netflix	3

33 rows × 22 columns

# TV Shows Available on at least 2 Platforms
print('\nTotal ', df_tvshows_ott[df_tvshows_ott['OTT Count'] == 2].shape[0], ' Titles are available on at least 2 Platforms\n')
tvshows_on_2_platforms = df_tvshows_ott[df_tvshows_ott['OTT Count'] == 2]
tvshows_on_2_platforms

Total  327  Titles are available on at least 2 Platforms

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
7	8	Retribution	2015	NR	7	28	NA	Joanna Vanderham,John Lynch,Joe Dempsie,Julie ...	Drama,Mystery,Thriller	United Kingdom	...	231	tv series	1	1	0	1	0	1	Netflix	2
15	16	Eli	2019	18	7.9	46	NA	Sacha Baron Cohen,Hadar Ratzon Rotem,Yael Eita...	Drama,History	France	...	53	tv series	1	1	0	1	0	1	Netflix	2
16	17	The Oath	2016	NR	6.6	88	NA	Ryan Kwanten,Katrina Law,Cory Hardrict,Joseph ...	Crime,Drama	United States	...	60	tv series	2	1	1	0	0	1	Netflix	2
17	18	Zero	2018	NR	5.5	88	Aanand L. Rai	Giuseppe Dave Seke,Haroun Fall,Beatrice Grannò...	Action,Comedy,Drama,Fantasy,Sci-Fi	Italy	...	164	tv series	1	1	0	1	0	1	Netflix	2
18	19	The Outsider	2018	NR	7.8	36	NA	Ben Mendelsohn,Bill Camp,Jeremy Bobb,Mare Winn...	Crime,Drama,Fantasy,Mystery,Thriller	United States	...	60	tv series	1	1	0	1	0	1	Netflix	2
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
3680	3681	Rudy Maxa's Travel	2001	0	7.8	NA	NA	Rudy Maxa,Kanoelehua Miller	Documentary	United States	...	30	tv series	5	0	1	1	0	1	Prime Video	2
3697	3698	WIRED's Autocomplete Interviews	2016	NR	NA	NA	NA	NA	NA	NA	...	NA	tv series	1	0	1	1	0	1	Prime Video	2
3698	3699	Out of Office with Brent Rose	2015	NR	NA	NA	NA	Brent Rose	Documentary	United States	...	NA	tv series	1	0	1	1	0	1	Prime Video	2
3707	3708	Bogus Beauty	2017	NR	NA	NA	NA	Selorm Kploanyi,Chrissy Mahlmeister	Comedy	United States	...	NA	tv series	1	0	1	1	0	1	Prime Video	2
3714	3715	pocket.watch Challenge Squad	2018	NR	4.4	NA	NA	Vitaly Gk,Jetta Juriansz,Brandi Say,Dalton Alf...	Family	United States	...	23	tv series	1	0	1	1	0	1	Prime Video	2

327 rows × 22 columns

# TV Shows Available on at least 1 Platform
print('\nTotal ', df_tvshows_ott[df_tvshows_ott['OTT Count'] == 1].shape[0], ' Titles are available on at least 1 Platforms\n')
tvshows_on_1_platforms = df_tvshows_ott[df_tvshows_ott['OTT Count'] == 1]
tvshows_on_1_platforms

Total  5072  Titles are available on at least 1 Platforms

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
0	1	Snowpiercer	2013	18	6.9	94	NA	Daveed Diggs,Iddo Goldberg,Mickey Sumner,Aliso...	Action,Drama,Sci-Fi,Thriller	United States	...	60	tv series	3	1	0	0	0	1	Netflix	1
1	2	Philadelphia	1993	13	8.8	80	NA	Charlie Day,Glenn Howerton,Rob McElhenney,Kait...	Comedy	United States	...	22	tv series	18	1	0	0	0	1	Netflix	1
2	3	Roma	2018	18	8.7	93	NA	Kevin McKidd,Ray Stevenson,Polly Walker,Kerry ...	Action,Drama,History,Romance,War	United Kingdom,United States	...	52	tv series	2	1	0	0	0	1	Netflix	1
4	5	The Young Offenders	2016	NR	8	100	NA	Alex Murphy,Chris Walley,Hilary Rose,Dominic M...	Comedy	United Kingdom,Ireland	...	30	tv series	3	1	0	0	0	1	Netflix	1
5	6	Suburra	2015	NR	7.9	91	NA	Alessandro Borghi,Giacomo Ferrara,Filippo Nigr...	Action,Crime	Italy	...	50	tv series	3	1	0	0	0	1	Netflix	1
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
5427	5428	Awesome Animals	2013	13	NA	NA	NA	Jake Cuddemi,Alex Wild	NA	NA	...	NA	tv series	1	0	0	0	1	1	Disney+	1
5428	5429	Tut's Treasures: Hidden Secrets	2018	13	7.4	NA	NA	Aidan Dodson,Salima Ikram,Paul Mercier,Chris N...	Documentary,History	United Kingdom	...	NA	tv series	1	0	0	0	1	1	Disney+	1
5429	5430	Wild Russia	2018	7	8.4	NA	NA	Christian Brückner,Jason Hildebrandt,Paterson ...	Documentary	Germany	...	360	tv series	2	0	0	0	1	1	Disney+	1
5430	5431	Love & Vets	2017	13	8.6	NA	NA	Will Draper,Francoise Tyler,Olivia,Carrie McCo...	Reality-TV	United States	...	42	tv series	1	0	0	0	1	1	Disney+	1
5431	5432	United States of Animals	2016	13	6.3	NA	NA	Quincy Dunn-Baker,Jo Mendenhall,Dale Anderson,...	NA	United States	...	22	tv series	1	0	0	0	1	1	Disney+	1

5072 rows × 22 columns

df_netflix_only_tvshows_ott = df_tvshows_ott[(df_tvshows_ott['Netflix'] == 1) & (df_tvshows_ott['Hulu'] == 0) & (df_tvshows_ott['Prime Video'] == 0 ) & (df_tvshows_ott['Disney+'] == 0)]
df_hulu_only_tvshows_ott = df_tvshows_ott[(df_tvshows_ott['Netflix'] == 0) & (df_tvshows_ott['Hulu'] == 1) & (df_tvshows_ott['Prime Video'] == 0 ) & (df_tvshows_ott['Disney+'] == 0)]
df_prime_video_only_tvshows_ott = df_tvshows_ott[(df_tvshows_ott['Netflix'] == 0) & (df_tvshows_ott['Hulu'] == 0) & (df_tvshows_ott['Prime Video'] == 1 ) & (df_tvshows_ott['Disney+'] == 0)]
df_disney_only_tvshows_ott = df_tvshows_ott[(df_tvshows_ott['Netflix'] == 0) & (df_tvshows_ott['Hulu'] == 0) & (df_tvshows_ott['Prime Video'] == 0 ) & (df_tvshows_ott['Disney+'] == 1)]

# TV Shows Available only on Netflix

print('\nTotal ', df_netflix_only_tvshows_ott['Title'].shape[0], ' Titles are available only on Netflix\n')

df_netflix_only_tvshows_ott

Total  1668  Titles are available only on Netflix

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
0	1	Snowpiercer	2013	18	6.9	94	NA	Daveed Diggs,Iddo Goldberg,Mickey Sumner,Aliso...	Action,Drama,Sci-Fi,Thriller	United States	...	60	tv series	3	1	0	0	0	1	Netflix	1
1	2	Philadelphia	1993	13	8.8	80	NA	Charlie Day,Glenn Howerton,Rob McElhenney,Kait...	Comedy	United States	...	22	tv series	18	1	0	0	0	1	Netflix	1
2	3	Roma	2018	18	8.7	93	NA	Kevin McKidd,Ray Stevenson,Polly Walker,Kerry ...	Action,Drama,History,Romance,War	United Kingdom,United States	...	52	tv series	2	1	0	0	0	1	Netflix	1
4	5	The Young Offenders	2016	NR	8	100	NA	Alex Murphy,Chris Walley,Hilary Rose,Dominic M...	Comedy	United Kingdom,Ireland	...	30	tv series	3	1	0	0	0	1	Netflix	1
5	6	Suburra	2015	NR	7.9	91	NA	Alessandro Borghi,Giacomo Ferrara,Filippo Nigr...	Action,Crime	Italy	...	50	tv series	3	1	0	0	0	1	Netflix	1
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
2252	2253	The Polar Sea	2014	NR	6.9	NA	NA	Gordon Pinsent,George Kourounis	Documentary	Canada	...	43	tv series	1	1	0	0	0	1	Netflix	1
2253	2254	JingleKids	2019	7	7.9	NA	NA	Prokhor Chekhovskoy,Sergey Druzyak,Sofya Lebed...	Animation,Adventure,Comedy,Family	Russia	...	11	tv series	2	1	0	0	0	1	Netflix	1
2254	2255	Sin Ellas No Hay Paraíso	2013	18	7	NA	NA	Carmen Villalobos,Catherine Siachoque,María Fe...	Action,Crime,Drama,Romance	Colombia,Mexico,United States	...	45	tv series	1	1	0	0	0	1	Netflix	1
2255	2256	Slice of Paradise	2017	NR	NA	NA	NA	Shelley Ferguson	NA	NA	...	NA	tv series	1	1	0	0	0	1	Netflix	1
2256	2257	Two Fathers	2013	NR	7.7	NA	NA	Lucia Hsieh,Weber Yang,Megan Lai,Marcus Chang,...	Drama	Taiwan	...	50	tv series	1	1	0	0	0	1	Netflix	1

1668 rows × 22 columns

# TV Shows Available only on Hulu

print('\nTotal ', df_hulu_only_tvshows_ott['Title'].shape[0], ' Titles are available only on Hulu\n')

df_hulu_only_tvshows_ott

Total  1308  Titles are available only on Hulu

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
101	102	Vice	2018	18	8.3	46	NA	Julia Louis-Dreyfus,Anna Chlumsky,Tony Hale,Re...	Comedy	United States	...	28	tv series	7	0	1	0	0	1	Hulu	1
102	103	Get Smart	2008	13	8.2	51	Peter Segal	Don Adams,Barbara Feldon,Edward Platt,Robert K...	Action,Adventure,Comedy,Crime,Family,Mystery,S...	United States	...	25	tv series	5	0	1	0	0	1	Hulu	1
103	104	Amazing Grace	2018	0	7.1	67	Michael Apted	Kate Jenkinson,Sigrid Thornton,Alex Dimitriade...	Drama	Australia	...	118	tv series	1	0	1	0	0	1	Hulu	1
104	105	Whitney	2018	18	5.7	88	NA	Whitney Cummings,Chris D'Elia,Rhea Seehorn,Zoe...	Comedy	United States	...	30	tv series	2	0	1	0	0	1	Hulu	1
105	106	Please Stand By	2018	13	8.2	56	NA	Bob Johnson,Ben Wright,William Douglas,Robert ...	Fantasy,Horror,Sci-Fi,Drama,Mystery,Thriller	United States	...	51	tv series	2	0	1	0	0	1	Hulu	1
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
3709	3710	pocket.watch CaptainSparklez mishmash	2018	NR	NA	NA	NA	Jordan Maron,Jetta Juriansz,Vitaly Gk	Family	United States	...	NA	tv series	1	0	1	0	0	1	Hulu	1
3710	3711	Newsy	2016	NR	NA	NA	NA	Katherine Biek,Julia Davis,Chance Seales	News	United States	...	NA	tv series	1	0	1	0	0	1	Hulu	1
3711	3712	Modd Couples	2016	18	5.3	NA	NA	Jim Colucci,Frank DeCaro,Pamela Hill,William J...	Comedy	United States	...	NA	tv series	1	0	1	0	0	1	Hulu	1
3712	3713	Fantasy Forecast	2016	NR	NA	NA	NA	NA	NA	United States	...	4	tv series	1	0	1	0	0	1	Hulu	1
3713	3714	Secret Talent Theatre	2016	NR	NA	NA	NA	NA	NA	NA	...	NA	tv series	1	0	1	0	0	1	Hulu	1

1308 rows × 22 columns

# TV Shows Available only on Prime Video

print('\nTotal ', df_prime_video_only_tvshows_ott['Title'].shape[0], ' Titles are available only on Prime Video\n')

df_prime_video_only_tvshows_ott

Total  1938  Titles are available only on Prime Video

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
125	126	Nosferatu	1922	NR	6.7	97	NA	Ashleigh Cummings,Ólafur Darri Ólafsson,Jahkar...	Drama,Fantasy,Horror,Mystery	United States	...	60	tv series	2	0	0	1	0	1	Prime Video	1
126	127	Three Days of the Condor	1975	18	7.7	87	NA	Max Irons,Kristen Hager,Bob Balaban,Sam McCart...	Action,Drama,Thriller	United States	...	60	tv series	2	0	0	1	0	1	Prime Video	1
127	128	Woody Allen: A Documentary	2011	NR	7.7	90	Robert B. Weide	Woody Allen,Letty Aronson,Marshall Brickman,Jo...	Documentary,Biography	United States	...	192	tv series	1	0	0	1	0	1	Prime Video	1
128	129	City of Ghosts	2017	18	8	98	Matt Dillon	Angel Chipagua,Sandra Equihua,Isa Fabro,Judy H...	Animation,Adventure,Family,Fantasy	United States	...	20	tv series	1	0	0	1	0	1	Prime Video	1
129	130	Proof	1991	18	7.5	65	NA	Eric McCormack,Rachael Leigh Cook,Kelly Rowan,...	Crime,Drama,Mystery,Thriller	United States	...	42	tv series	3	0	0	1	0	1	Prime Video	1
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
5291	5292	Sawyer Sessions	2015	NR	NA	NA	Stéphan Aubé	Guillaume Connesson	Music	Denmark	...	3	tv series	1	0	0	1	0	1	Prime Video	1
5292	5293	Pinkfong! Dinosaur Songs	2014	NR	NA	NA	NA	NA	NA	NA	...	NA	tv series	2	0	0	1	0	1	Prime Video	1
5293	5294	How To Self-Publish	2017	NR	NA	NA	NA	Jean-François Gariépy	News	NA	...	NA	tv series	1	0	0	1	0	1	Prime Video	1
5294	5295	BigDo2 - Random Hair	2016	NR	NA	NA	NA	NA	NA	NA	...	NA	tv series	1	0	0	1	0	1	Prime Video	1
5295	5296	We`ll Talk When You Get Back	2015	NR	NA	NA	NA	Elena Drobysheva,Aleksandra Evchenko,Andrey Fe...	Drama,Romance	Russia	...	NA	tv series	1	0	0	1	0	1	Prime Video	1

1938 rows × 22 columns

# TV Shows Available only on Disney+

print('\nTotal ', df_disney_only_tvshows_ott['Title'].shape[0], ' Titles are available only on Disney+\n')

df_disney_only_tvshows_ott

Total  158  Titles are available only on Disney+

	ID	Title	Year	Age	IMDb	Rotten Tomatoes	Directors	Cast	Genres	Country	...	Runtime	Kind	Seasons	Netflix	Hulu	Prime Video	Disney+	Type	Service Provider	OTT Count
482	483	Avatar	2009	13	9.2	82	NA	Dee Bradley Baker,Zach Tyler,Mae Whitman,Jack ...	Animation,Action,Adventure,Family,Fantasy,Mystery	United States	...	23	tv series	3	0	0	0	1	1	Disney+	1
483	484	Invincible	2006	7	8.8	72	Angelina Jolie	Steven Yeun,Sandra Oh,J.K. Simmons,Zazie Beetz...	Animation,Action,Adventure,Drama,Fantasy,Horro...	United States	...	137	tv series	1	0	0	0	1	1	Disney+	1
484	485	High School Musical	2006	0	7.4	63	Kenny Ortega	Joshua Bassett,Olivia Rodrigo,Matt Cornett,Jul...	Comedy,Drama,Musical	United States	...	31	tv series	2	0	0	0	1	1	Disney+	1
485	486	Ruby Bridges	1998	7	7.2	83	Euzhan Palcy	Penelope Ann Miller,Kevin Pollak,Michael Beach...	Adventure,Comedy,Drama,Family,Fantasy	United States	...	96	tv series	1	0	0	0	1	1	Disney+	1
486	487	Stargirl	2020	7	7.3	70	NA	Brec Bassinger,Yvette Monreal,Anjelika Washing...	Action,Adventure,Crime,Drama,Fantasy,Sci-Fi	United States	...	566	tv series	2	0	0	0	1	1	Disney+	1
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
5427	5428	Awesome Animals	2013	13	NA	NA	NA	Jake Cuddemi,Alex Wild	NA	NA	...	NA	tv series	1	0	0	0	1	1	Disney+	1
5428	5429	Tut's Treasures: Hidden Secrets	2018	13	7.4	NA	NA	Aidan Dodson,Salima Ikram,Paul Mercier,Chris N...	Documentary,History	United Kingdom	...	NA	tv series	1	0	0	0	1	1	Disney+	1
5429	5430	Wild Russia	2018	7	8.4	NA	NA	Christian Brückner,Jason Hildebrandt,Paterson ...	Documentary	Germany	...	360	tv series	2	0	0	0	1	1	Disney+	1
5430	5431	Love & Vets	2017	13	8.6	NA	NA	Will Draper,Francoise Tyler,Olivia,Carrie McCo...	Reality-TV	United States	...	42	tv series	1	0	0	0	1	1	Disney+	1
5431	5432	United States of Animals	2016	13	6.3	NA	NA	Quincy Dunn-Baker,Jo Mendenhall,Dale Anderson,...	NA	United States	...	22	tv series	1	0	0	0	1	1	Disney+	1

158 rows × 22 columns

ott_group_count = df_tvshows_ott.groupby('OTT Count')['Title'].count()
ott_group_tvshows = df_tvshows_ott.groupby('OTT Count')[['Netflix', 'Hulu', 'Prime Video', 'Disney+']].sum()
ott_group_data_tvshows = pd.concat([ott_group_count, ott_group_tvshows], axis = 1).reset_index().rename(columns = {'Title' : 'TV Shows Count'})
ott_group_data_tvshows = ott_group_data_tvshows.sort_values(by = 'TV Shows Count', ascending = False)

ott_group_data_tvshows

	OTT Count	TV Shows Count	Netflix	Hulu	Prime Video	Disney+
0	1	5072	1668	1308	1938	158
1	2	327	153	257	222	22
2	3	33	33	32	31	3

# Title Group with TV Shows Counts - All Platforms Combined
ott_group_data_tvshows.sort_values(by = 'TV Shows Count', ascending = False)

	OTT Count	TV Shows Count	Netflix	Hulu	Prime Video	Disney+
0	1	5072	1668	1308	1938	158
1	2	327	153	257	222	22
2	3	33	33	32	31	3

ott_group_data_tvshows.sort_values(by = 'OTT Count', ascending = False)

	OTT Count	TV Shows Count	Netflix	Hulu	Prime Video	Disney+
2	3	33	33	32	31	3
1	2	327	153	257	222	22
0	1	5072	1668	1308	1938	158

fig = px.bar(y = ott_group_data_tvshows['TV Shows Count'],
             x = ott_group_data_tvshows['OTT Count'], 
             color = ott_group_data_tvshows['OTT Count'],
             color_continuous_scale = 'Teal_r', 
             labels = { 'y' : 'TV Shows Count', 'x' : 'OTT Count'},
             title  = 'TV Shows with Group Title : All Platforms')
fig.update_layout(plot_bgcolor = "white")
fig.show()

fig = px.pie(ott_group_data_tvshows,
             names = ott_group_data_tvshows['OTT Count'],
             values = ott_group_data_tvshows['TV Shows Count'],
             color = ott_group_data_tvshows['TV Shows Count'],
             color_discrete_sequence = px.colors.sequential.Teal)

fig.update_traces(textinfo = 'percent+label',
                  title = 'TV Shows Count based on OTT Count')
fig.show()